Ignite Creation Date:
2025-12-24 @ 7:41 PM
Ignite Modification Date:
2025-12-30 @ 11:58 PM
Study NCT ID:
NCT03960203
Status:
COMPLETED
Last Update Posted:
2019-05-24
First Post:
2019-05-17
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Effect of a Sepsis Prediction Algorithm on Clinical Outcomes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018805', 'term': 'Sepsis'}, {'id': 'D004194', 'term': 'Disease'}], 'ancestors': [{'id': 'D007239', 'term': 'Infections'}, {'id': 'D018746', 'term': 'Systemic Inflammatory Response Syndrome'}, {'id': 'D007249', 'term': 'Inflammation'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 75147}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2017-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2019-05', 'completionDateStruct': {'date': '2018-06', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2019-05-22', 'studyFirstSubmitDate': '2019-05-17', 'studyFirstSubmitQcDate': '2019-05-21', 'lastUpdatePostDateStruct': {'date': '2019-05-24', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2019-05-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2018-06', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'In-hospital mortality', 'timeFrame': '1 year', 'description': 'Rate of in-hospital mortality based on SIRS criteria'}], 'secondaryOutcomes': [{'measure': 'Hospital length of stay', 'timeFrame': '1 year', 'description': 'Duration of hospital length of stay in days based on SIRS criteria'}, {'measure': '30-day readmissions', 'timeFrame': '1 year', 'description': 'Rate of patient readmissions within 30 days'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Dascena', 'Patient mortality', 'Length of stay', 'Readmissions', 'Algorithm', 'Diagnostic', 'Clinical outcomes'], 'conditions': ['Severe Sepsis']}, 'referencesModule': {'references': [{'pmid': '32354696', 'type': 'DERIVED', 'citation': 'Burdick H, Pino E, Gabel-Comeau D, McCoy A, Gu C, Roberts J, Le S, Slote J, Pellegrini E, Green-Saxena A, Hoffman J, Das R. Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals. BMJ Health Care Inform. 2020 Apr;27(1):e100109. doi: 10.1136/bmjhci-2019-100109.'}]}, 'descriptionModule': {'briefSummary': 'In this clinical outcomes analysis, the effect of a machine learning algorithm for severe sepsis prediction on in-hospital mortality, hospital length of stay, and 30-day readmission was evaluated.', 'detailedDescription': 'Materials and Methods: Clinical outcomes evaluation performed on a multiyear, multicenter clinical data set of real-world data containing 75,147 patient encounters from nine hospitals. Mortality, hospital length of stay, and 30-day readmission analysis performed for 17,758 adult patients who met two or more Systemic Inflammatory Response Syndrome (SIRS) criteria at any point during their stay.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* All patients over the age of 18 presenting to the emergency department or admitted to an inpatient unit at the participating facilities were automatically included for clinical outcomes analysis\n\nExclusion Criteria:\n\n* Patients under the age of 18'}, 'identificationModule': {'nctId': 'NCT03960203', 'briefTitle': 'Effect of a Sepsis Prediction Algorithm on Clinical Outcomes', 'organization': {'class': 'INDUSTRY', 'fullName': 'Dascena'}, 'officialTitle': 'Effect of a Sepsis Prediction Algorithm on Patient Mortality, Length of Stay, and Readmission', 'orgStudyIdInfo': {'id': '05172019'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Comparator', 'description': 'The comparator arm will involve patients monitored by InSight.', 'interventionNames': ['Diagnostic Test: InSight']}], 'interventions': [{'name': 'InSight', 'type': 'DIAGNOSTIC_TEST', 'description': 'Clinical decision support (CDS) system for severe sepsis detection and prediction', 'armGroupLabels': ['Comparator']}]}, 'contactsLocationsModule': {'overallOfficials': [{'name': 'Ritankar Das, MSc', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Dascena'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Dascena', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}